The Prediction Research of Safety Stock Based on the Combinatorial Forecasting Model

DOI

10.2991/iccse-15.2015.35How to use a DOI?

Keywords

Safety stock; Support vector machine (SVM); Radial basis function neural network (RBFNN); Genetic algorithm (GA) combination forecasting model

Abstract

The inventory is related to enterprise’s production, sales and cash flow. Therefore, enterprises pay more and more attention to safety stock control. In this paper, on the basis of support vector machine (SVM) model and RBF neural network model, genetic algorithm (GA) combined forecasting model is established for enterprise safety stock prediction research. The example analysis results show that the predicted results of combined forecasting model is accurate, and it’s a scientific, reasonable and effective method for safety stock predictive control.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Weiping Zhong
AU  - Lili Zhang
PY  - 2015/07
DA  - 2015/07
TI  - The Prediction Research of Safety Stock Based on the Combinatorial Forecasting Model
BT  - Proceedings of the 2015 International Conference on Computational Science and Engineering
PB  - Atlantis Press
SP  - 200
EP  - 206
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-15.2015.35
DO  - 10.2991/iccse-15.2015.35
ID  - Zhong2015/07
ER  -